Automic Helps DevOps Transformation Sparkle

Working closely with Automic, an international wholesaler and retailer of jewelery transformed a department of project managers, developers and operations responsible for all of the customer-facing websites into a DevOps organization. As a result, project delivery was completed with 90 percent fewer delays, and first customer-facing releases of projects could be delivered in less than half the time. The usability of its websites increased significantly, resulting in more customer traffic, longer average time spent on the sites and increased revenue.

Haphazard Development

Prior to the DevOps implementation, new projects were delivered by “waterfall” project management means. The cyclical resource planning process was based on the project portfolio and business priorities. Project managers then planned project milestones working closely with business stakeholders, business analysts and application developers. Analysts created specifications and developers were assigned to work on packages and tasks to implement them.

Different web technologies were used with varying levels of dev and ops expertise in each technology. The Operations team members usually fulfilled requests made during the course of a project as part of their overall daily tasks—for example, to provision a new environment, deploy a package or change the environment configuration.

This approach had a major disadvantage. Delays in one project impacted the overall resource planning and could have a cascading effect on other projects. Delays in projects could be for multiple reasons, such as waiting for business stakeholder impact, frequently changing requirements, unexpected sick leaves of developers or poor estimates. Other frequent causes included delays in operations tasks such as a deployment or provisioning of a new environment. These delays were caused by unaligned planning as well as a mismatch in priorities between projects and operations. Besides delays, some developers were underutilized, which also was exacerbated because they were specialized in a technology or component.

DevOps Transformation Solution

Working closely with the customer, Automic restructured dev and ops by:

Switching the development from a project to a product mode (cross-project development teams based on capabilities rather than assignment of individual developers to projects).

Moving project managers from development micromanagement to focus on major milestones and deliverables to the business.

Organizing both dev and ops into multiskilled teams focused on individual products rather than technologies.

Aligning ops into delivery teams, initially part-time and later full-time.

Giving delivery teams the end-to-end responsibility for their products, including their operations.

Standardizing the technology stacks within teams (but not across them) over time.

Delivering projects into production (or alpha, beta) in slices (releases) instead of just once to get early feedback and improve.

Results: Fewer Delays, Better Usability

By standardizing, this customer has transformed its dev and ops teams, creating an agile, scalable environment that can drive the business forward. The company achieved the following specific results:

Project delivery are now completed with 90 percent fewer delays. First customer-facing releases of projects now are usually delivered in less than half time.

The usability of websites has increased significantly, resulting in more customer traffic, customers remaining longer on the sites and increased revenue opportunities.

About the Author/Michael Schmidt

Michael Schmidt heads DevOps Practice at Automic, a management and technology advisory service established to help Automic customers to prepare for and transform their organizations toward DevOps. Michael spent his carrier as consultant, entrepreneur and in several product-related leadership positions. He has a passion for building lean IT organizations. Michael holds a joint MBA from New York University, London School of Economics and HEC Paris and a Master of Computing Science.

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